Current Trends on Data Management

Dear Colleagues,

We live in a highly data-driven digital-first era. The creation of high volumes of data leads to the formation of large repositories, which necessitate the development of novel techniques to analyze, process and structure these data. The term "data management" pertains to the processes and procedures employed in handling data and involves creating, implementing, and overseeing plans, policies, programs, and practices that ensure the proper delivery, control, protection, and enhancement of the value of data and information assets over their entire lifespan.

New trends in cloudification, microservices, open data, or software as a service (SaaS) approaches, among others, have a significant impact on data management. In parallel, new approaches to Artificial Intelligence (AI), Machine Learning (ML), and Natural Language Processing (NLP) require the management of increasingly large amounts of datasets (e.g., Large Language Models, LLMs) and synthetic data (i.e., artificially generated data).

The main objective of this Special Issue is to bring together novel and impactful research on data management and the adoption of these techniques for practical applications. Specific topics of interest include, but are not limited to, the following:

• Data governance;
• Data storage and operations;
• Data integration and interoperability;
• Data confidentiality;
• Data security and protection;
• Data architecture and infrastructure;
• Synthetic data ;
• Open data.

Dr. Boni García
Prof. Dr. Mario Munoz-Organero
Dr. Patricia Callejo
Prof. Miguel Ángel Hombrados
Guest Editors

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